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Overview of Data Mining and Predictive Modelling
 
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My web page: www.imperial.ac.uk/people/n.sadawi The slides can be found here: https://github.com/nsadawi/DataMiningSlides
Views: 126745 Noureddin Sadawi
Predictive Data Analytics in UNDER 5 Minutes
 
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For NeuroSolutions Infinity software, visit: http://www.neurosolutions.com/infinity/ Download the FREE Trial: http://www.neurosolutions.com/downloads/ What is Predictive Data Analytics? Learn in under 5 minutes. This video is an introduction to Predictive Data Analytics development methodology. By the end of this video, you'll understand the core concepts of predictive data analytics. You'll be able to get started implementing it into your own custom software solutions.
Views: 54812 NeuroDimension
Data Analytics - Descriptive , Predictive and Prescriptive Analytics
 
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@ Members ~ This video would let you know about rising importance of Analytics where by we are covering all 4 Branches of Analytics like Financial Analytics , Risk Based Analytics , Cash Flow Analytics and Data Analytics. Video would also let you know about 3 types of Analytics covering Descriptive Analytics , Predictive Analytics and Prescriptive Analytics. You are most welcome to connect with us at 91-9899242978 (Handheld) , Skype ~ Rahul5327 , Twitter @ Rahulmagan8 , [email protected] , [email protected] or visit our website - www.treasuryconsulting.in
What's difference?(Big data, predictive analytics, data science, data mining, business intelligence)
 
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Download "Explore Me - Find everything nearby" App from playstore: https://play.google.com/store/apps/details?id=com.yogeshkorke.admin.exploreme This video describes the short difference between Big data analytics, predictive analytics, prescriptive analytics, descriptive analytics, business intelligence, data science, machine learning, data mining and their application with help of example store sales. Like, share and subscribe more such videos!
Views: 11183 CryptoZilla
AI for Marketing & Growth #1 - Predictive Analytics in Marketing
 
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AI for Marketing & Growth #1 - Predictive Analytics in Marketing Download our list of the world's best AI Newsletters 👉https://hubs.ly/H0dL7N60 Welcome to our brand new AI for Marketing & Growth series in which we’ll get you up to speed on Predictive Analytics in Marketing! This series you-must-watch-this-every-two-weeks sort of series or you’re gonna get left behind.. Predictive analytics in marketing is a form of data mining that uses machine learning and statistical modeling to predict the future. Based on historical data. Applications in action are all around us already. For example, If your bank notifies you of suspicious activity on your bank card, it is likely that a statistical model was used to predict your future behavior based on your past transactions. Serious deviations from this pattern are flagged as suspicious. And that’s when you get the notification. So why should marketers care? Marketers can use it to help optimise conversions for their funnels by forecasting the best way to move leads down the different stages, turning them into qualified prospects and eventually converting them into paying customers. Now, if you can predict your customers’ behavior along the funnel, you can also think of messages to best influence that behavior and reach your customer’s highest potential value. This is super-intelligence for marketers! Imagine if you could not only determine whether a lead is a good fit for your product but also which are most promising. This’ll allow you to focus your team’s efforts on leads with the highest ROI. Which will also imply a shift in mindset. Going from quantity metrics, or how many leads you can attract, to quality metrics, or how many good leads you can engage. You can now easily predict your OMTM or KPIs in real-time and finally push vanity metrics aside. For example, based on my location, age, past purchases, and gender, how likely are you to buy eggs I if you just added milk to your basket? A supermarket can use this information to automatically recommend products to you A financial services provider can use thousands of data points created by your online behaviour to decide which credit card to offer you, and when. A fashion retailer can use your data to decide which shoes to recommend as your next purchase, based on the jacket you just bought. Sure, businesses can improve their conversion rates, but the implications are much bigger than that. Predictive analytics allows companies to set pricing strategies based on consumer expectations and competitor benchmarks. Retailers can predict demand, and therefore make sure they have the right level of stock for each of their products. The evidence of this revolution is already around us. Every time we type a search query into Google, Facebook or Amazon we’re feeding data into the machine. The machine thrives on data, growing ever more intelligent. To leverage the potential of artificial intelligence and predictive analytics, there are four elements that organizations need to put into place. 1. The right questions 2. The right data 3. The right technology 4. The right people Ok.. let’s look at some use cases of businesses that are already leveraging predictive analytics. Other topics discussed: Ai analytics case study artificial intelligence big data deep learning demand forecasting forecasting sales machine learning predictive analytics in marketing data mining statistical modelling predict the future historical data AI Marketing machine learning marketing machine learning in marketing artificial intelligence in marketing artificial intelligence AI Machine learning ------------------------------------------------------- Amsterdam bound? Want to make AI your secret weapon? Join our A.I. for Marketing and growth Course! A 2-day course in Amsterdam. No previous skills or coding required! https://hubs.ly/H0dkN4W0 OR Check out our 2-day intensive, no-bullshit, skills and knowledge Growth Hacking Crash Course: https://hubs.ly/H0dkN4W0 OR our 6-Week Growth Hacking Evening Course: https://hubs.ly/H0dkN4W0 OR Our In-House Training Programs: https://hubs.ly/H0dkN4W0 OR The world’s only Growth & A.I. Traineeship https://hubs.ly/H0dkN4W0 Make sure to check out our website to learn more about us and for more goodies: https://hubs.ly/H0dkN4W0 London Bound? Join our 2-day intensive, no-bullshit, skills and knowledge Growth Marketing Course: https://hubs.ly/H0dkN4W0 ALSO! Connect with Growth Tribe on social media and stay tuned for nuggets of wisdom, updates and more: Facebook: https://www.facebook.com/GrowthTribeIO/ LinkedIn: https://www.linkedin.com/company/growth-tribe Twitter: https://twitter.com/GrowthTribe/ Instagram: https://www.instagram.com/growthtribe/ Snapchat: growthtribe Video URL: https://youtu.be/uk82DHcU7z8
Views: 23104 Growth Tribe
Top 5 Algorithms used in Data Science | Data Science Tutorial | Data Mining Tutorial | Edureka
 
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( Data Science Training - https://www.edureka.co/data-science ) This tutorial will give you an overview of the most common algorithms that are used in Data Science. Here, you will learn what activities Data Scientists do and you will learn how they use algorithms like Decision Tree, Random Forest, Association Rule Mining, Linear Regression and K-Means Clustering. To learn more about Data Science click here: http://goo.gl/9HsPlv The topics related to 'R', Machine learning and Hadoop and various other algorithms have been extensively covered in our course “Data Science”. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 109740 edureka!
Predictive Analytics using Orange Data Mining
 
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Data Mining Fruitful and Fun Open source machine learning and data visualization for novice and expert. Interactive data analysis workflows with a large toolbox. Download Link: https://orange.biolab.si/download/
Views: 5054 Anurag P
The Fundamentals of Predictive Analytics - Data Science Wednesday
 
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Data Science Wednesday is produced by Decisive Data, a data analytics consultancy. Lean more about us using the following links. Also, the video transcription is included below. http://www.decisivedata.net https://twitter.com/DecisiveData https://www.linkedin.com/company/decisive-data/ Video Transcription: What is Predictive Analytics Hello, and welcome back to Data Science Wednesday. My name is Tessa Jones, and I'm a data scientist with Decisive Data. And today we're gonna talk about predictive analytics and what it can do for you. Predictive analytics fits into the spectrum of analytics that we've talked about before. Starting with descriptive, which is the most basic of the analytics, it's basically just cleaning, relating, summarizing, and visualizing your data, really getting to the questions about what's happening in my business. And then there's diagnostic, which is really getting down to why things are happening. What's causing my revenue to decline or to increase? How are things related? Things like that. So if you've got a good base in both of these, then we're ready to move into predictive analytics, which is gonna dive into what's gonna happen in the future, which is super powerful. If you're a business person and you want to be able to make good business questions, if you have at least an idea of what might happen in the future, your answers are already gonna be a little bit better. So, let's dive in. So, let's go with an example because that just makes it easier to kind of flow through what's actually happening here. So let's pretend that we are grocery store owners. And if we're already talking about predictive analytics, you should have a pretty good grasp on descriptive and predictive and diagnostic analytics. So, you probably already have a decent dashboard that really tells you what's happening in your business right now. So, something like this where you have, you know, something here that tells you revenue by different departments like foods and pastry, or how your sales changes by product over time, things like that. So you have an idea of what's happening in your business, but now you really wanna know, what's gonna happen in my business? So one really common question is, how many of a given product am I gonna sell for every store? Because this can really answer questions around how you're gonna support supply chain processes, or how you're gonna manage the profits that you're going to have. Things like that. So the first thing we need to do is talk about what happened in the past. We really can't do anything or predict very easily unless we know or at least have an idea of what's happened in the past. So here we have three lines in black that represent, basically, historical data. Each line here is one year worth of sales for a given product. And then the green line here is the current year. And here's today. And if we build a predictive model, it's gonna tell us what's gonna happen for the rest of the year. So if this is all set up and we build a model, basically, we mix this information with all the data that's really clean and well-organized, we mash it together with a bunch of mathematics and coding, and basically, we pop out some results and it shows up in a visual like this where you have, these are the sales that we have had and these are the sales that we think we're going to have. So a business person can look at this chart and say, "Wow, we need to put a lot more products to this store because I see sales are gonna increase." Or, "Our profit margins are gonna be way higher than we thought so we can start a new program." Things like that. You can really start to get innovative with your business decisions. So, let's pretend we've built this model and it's been running for a year. And now we wanna know how well is this model actually performing? So down here, we have a chart that shows, in black, what we actually sold, and then in green, what we thought we were going to sell. And we see that there's a couple of pretty big misses. Right here, we sold way more than we thought we would, which leaves risk to, you know, missing out on inventory. Or, here, we predicted we would sell way more than we did. So both of these are kind of misses. And so we need to go back and look at the data and understand what assumptions we applied that were maybe a little bit wrong, or applied incorrectly, or look at the data, maybe we weren't accounting for something and we kind of reorganize that and incorporate it into the model. And then we redeploy it, and then we have a better model.
Views: 7853 Decisive Data
What is PREDICTIVE ANALYTICS? What does PREDICTIVE ANALYSIS mean? PREDICTIVE ANALYSIS meaning
 
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What is PREDICTIVE ANALYTICS? What does PREDICTIVE ANALYSIS mean? PREDICTIVE ANALYSIS meaning - PREDICTIVE ANALYTICS definition - PREDICTIVE ANALYTICS explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. Predictive analytics encompasses a variety of statistical techniques from predictive modeling, machine learning, and data mining that analyze current and historical facts to make predictions about future or otherwise unknown events. In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision making for candidate transactions. The defining functional effect of these technical approaches is that predictive analytics provides a predictive score (probability) for each individual (customer, employee, healthcare patient, product SKU, vehicle, component, machine, or other organizational unit) in order to determine, inform, or influence organizational processes that pertain across large numbers of individuals, such as in marketing, credit risk assessment, fraud detection, manufacturing, healthcare, and government operations including law enforcement. Predictive analytics is used in actuarial science, marketing, financial services, insurance, telecommunications, retail, travel, healthcare, child protection, pharmaceuticals, capacity planning and other fields. One of the best-known applications is credit scoring, which is used throughout financial services. Scoring models process a customer's credit history, loan application, customer data, etc., in order to rank-order individuals by their likelihood of making future credit payments on time. Predictive analytics is an area of data mining that deals with extracting information from data and using it to predict trends and behavior patterns. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future. For example, identifying suspects after a crime has been committed, or credit card fraud as it occurs. The core of predictive analytics relies on capturing relationships between explanatory variables and the predicted variables from past occurrences, and exploiting them to predict the unknown outcome. It is important to note, however, that the accuracy and usability of results will depend greatly on the level of data analysis and the quality of assumptions. Predictive analytics is often defined as predicting at a more detailed level of granularity, i.e., generating predictive scores (probabilities) for each individual organizational element. This distinguishes it from forecasting. For example, "Predictive analytics—Technology that learns from experience (data) to predict the future behavior of individuals in order to drive better decisions." In future industrial systems, the value of predictive analytics will be to predict and prevent potential issues to achieve near-zero break-down and further be integrated into prescriptive analytics for decision optimization. Furthermore, the converted data can be used for closed-loop product life cycle improvement which is the vision of the Industrial Internet Consortium.
Views: 1818 The Audiopedia
MicroStrategy - Data Mining & Predictive Analytics - Online Training Video by MicroRooster
 
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Source: MicroRooster.blogspot.com Format: A MicroStrategy Online Training Video blog. Description: An introduction to Data Mining & Predictive Analytics using MicroStrategy. This demo explains how to use MicroStrategy for performing advanced data science analysis. Must have some understanding of basic data mining to take advantage of this entry level demo.
Views: 17501 MicroRooster
Predictive Analytics in Insurance
 
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If you have questions or comments on the contents of this video, please email us at [email protected] There has been considerable change in the relationships between customers and companies. Customers are in control of the relationships with their vendors and are not afraid to switch to a new provider if they do not feel they are receiving the service they deserve. Companies now have the ability to know their customers and market to them on a personalized basis using data mining and predictive analytics technologies. Predictive Analytics unlock insights that enable companies to add new customers and grow their existing business by improving their understanding of what their customers want. It uncovers hidden insights in customer data to create more personalized customer experiences that win more business while reducing costs and increasing customer loyalty. Predictive Analytics enable the very sharpest competitive edge. They deliver powerful, unique, qualitative differentiation by providing your enterprise a proprietary source of business intelligence with which to compete in Operations, Customer or Threat & Fraud applications in your organization. A predictive model generated from your data taps into experience to which only your company is privy, since it is unique to your prospect list and to the product and marketing message to which your customers respond (both positively and negatively). Therefore, the model's intelligence and insights are outside the reaches of common knowledge, and the top prospects it flags compose a customized, proprietary contact list. View this informative webinar to learn more about how Predictive Analytics are making a difference in the insurance industry through focused target marketing, and more efficient fraudulent claim detection. We discuss a detailed use-case for a real-world insurance company examining how specific customer attributes were used as indicators for fraud prediction.
Views: 14202 LPA Software Solutions
Predicting Stock Prices with SSAS Mining Models
 
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Predictive analytics and supervised machine learning with SSAS and C#. In this demo I use MS Time Series Mining structure within SSAS to predict stock prices using the Auto Regressive Integrated Moving Average (ARIMA) method. This is a bit of supervised machine learning with analysis services. I then query the mining model with SSMS and run a prediction query from a C# applications
Views: 3757 sackdeezle
RapidMiner Tutorial - Overview of the Data Mining and Predictive Analytics
 
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A tutorial overview of RapidMiner, an open source system for data mining, predictive analytics, machine learning, and artificial intelligence applications. For more information: http://rapid-i.com/ Brought to you by Rapid Progress Marketing and Modeling, LLC (RPM Squared) http://www.RPMSquared.com/ www.RPMSquared.com
Views: 10441 Predictive Analytics
What is Predictive Analytics?
 
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Want to understand predictive analytics? Brad Hill, Product Marketing Manger for IBM SPSS Modeler explains what predictive analytics is, where it is used and how it works. IBM SPSS Modeler: https://ibm.biz/BdxmGt Video: https://ibm.biz/BdxT8v
Views: 102596 bradhill14
Introduction to Predictive Analytics
 
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Eric Siegel, Ph.D. Founder, Predictive Analytics World Author, Predictive Analytics
Views: 109971 UCIrvineDLC
RapidMiner Tutorial - Modeling and Scoring  (Data Mining and Predictive Analytics System)
 
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A tutorial discussing modeling and scoring in RapidMiner. RapidMiner is an open source system for data mining, predictive analytics, machine learning, and artificial intelligence applications. For more information: http://rapid-i.com/ Brought to you by Rapid Progress Marketing and Modeling, LLC (RPM Squared) http://www.RPMSquared.com/
Views: 6955 Predictive Analytics
Data Mining using R | Data Mining Tutorial for Beginners | R Tutorial for Beginners | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R tutorial on "Data Mining using R" will help you understand the core concepts of Data Mining comprehensively. This tutorial will also comprise of a case study using R, where you'll apply data mining operations on a real life data-set and extract information from it. Following are the topics which will be covered in the session: 1. Why Data Mining? 2. What is Data Mining 3. Knowledge Discovery in Database 4. Data Mining Tasks 5. Programming Languages for Data Mining 6. Case study using R Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #LogisticRegression #Datasciencetutorial #Datasciencecourse #datascience How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Website: https://www.edureka.co/data-science Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. " Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 84756 edureka!
Predicting Stock Prices - Learn Python for Data Science #4
 
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In this video, we build an Apple Stock Prediction script in 40 lines of Python using the scikit-learn library and plot the graph using the matplotlib library. The challenge for this video is here: https://github.com/llSourcell/predicting_stock_prices Victor's winning recommender code: https://github.com/ciurana2016/recommender_system_py Kevin's runner-up code: https://github.com/Krewn/learner/blob/master/FieldPredictor.py#L62 I created a Slack channel for us, sign up here: https://wizards.herokuapp.com/ Stock prediction with Tensorflow: https://nicholastsmith.wordpress.com/2016/04/20/stock-market-prediction-using-multi-layer-perceptrons-with-tensorflow/ Another great stock prediction tutorial: http://eugenezhulenev.com/blog/2014/11/14/stock-price-prediction-with-big-data-and-machine-learning/ This guy made 500K doing ML stuff with stocks: http://jspauld.com/post/35126549635/how-i-made-500k-with-machine-learning-and-hft Please share this video, like, comment and subscribe! That's what keeps me going. and please support me on Patreon!: https://www.patreon.com/user?u=3191693 Check out this youtube channel for some more cool Python tutorials: https://www.youtube.com/watch?v=RZF17FfRIIo Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 619464 Siraj Raval
Data Mining Classification and Prediction ( in Hindi)
 
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A tutorial about classification and prediction in Data Mining .
Views: 43010 Red Apple Tutorials
Employee Attrition Predictive Analysis - FOSSASIA Singapore OpenXLab Meetup
 
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Industrial Application of Data Science and Machine Learning on Employee Attrition Predictive Analysis Speaker: Le Zhang Employee Churn Predictive Analysis - This session will walk through an industry project that predicts employee churn through sentiment analysis. This is a real-world case that Microsoft Data Scientists had been working on, and has been deployed for real use. Through the practical case, we will share the methodologies, algorithms, techniques, tools used and the rational for such choices. Our Data Scientist will also share the R based data science solution accelerator that has been developed forboosting prototyping, documenting, and presenting R based data science projects, which can be of use in other projects. https://github.com/Microsoft/acceleratoRs/ About the speaker: Le Zhang is Data Scientist from Microsoft. He is with the Algorithms and Data Science Asia Pacific team, where he develops tools for machine learning on cloud and reusable solution templates that accelerate the process of resolving data science problems in various domains. He holds Ph. D. degree in Computer Engineering and he is a vim lover. Event Page: Produced by Engineers.SG Help us caption & translate this video! http://amara.org/v/4rrG/
Views: 2836 Engineers.SG
Big Data and predictive analysis: use case in the hotel industry
 
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In order to improve its offer in a business strongy challenged by new players who offer new hosting modal. A hotel company intends to implement a Big Data solution that can predict hotel occupancy so that rates can be optimized according to demand. Discover how this hotel company has implemented a predictive analysis tool with no previous experience in Big Data thanks to Public Cloud and Orange Business Services experts. More about Orange Business Services: Official website: http://www.orange-business.com/en Facebook: https://www.facebook.com/orangebusiness/ Twitter: https://twitter.com/orangebusiness Linkedin: https://www.linkedin.com/company/oran... Slideshare: http://www.slideshare.net/orangebusiness Pinterest: https://fr.pinterest.com/orangebusiness
Applications of Predictive Analytics in Legal | Litigation Analytics, Data Mining & AI | Great Lakes
 
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#PredictiveAnalytics | Learn the prediction of outcome or treatment of a case by legal courts of Appeals based on historical data using predictive analytics. Watch the video to understand analytics in legal using case study on real-life data set. How litigation analytics can flourish with the use of data mining and AI. Know more about our analytics Program: PGP- Business Analytics: https://goo.gl/V9RzVD PGP- Big Data Analytics: https://goo.gl/rRyjj4 Business Analytics Certification Program: https://goo.gl/7HPoUY #LegalTech #LegalAnalytics #GreatLearning #GreatLakes About Great Learning: - Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about the pillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU - For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 - Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: - Google Plus: https://plus.google.com/u/0/108438615307549697541 - Facebook: https://www.facebook.com/GreatLearningOfficial/ - LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/?utm_source=Youtube Great Learning has collaborated with the University of Texas at Austin for the PG Program in Artificial Intelligence and Machine Learning and with UT Austin McCombs School of Business for the PG Program in Analytics and Business Intelligence.
Views: 1208 Great Learning
Predictive Data Mining For Sugar Crop Yield Prediction With Irrigation And Pesticide Usage Support
 
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Predictive Data Mining Technique to correlate weather data with Sugar Crop pest density. This correlate the rules for best yield from Sugar Crop par acre area with current weather data to estimate the accurate requirement for Drip and Conventional irrigation, Asiphate PPM to ensure high yield.
Views: 2379 rupam rupam
Data Mining and Predictive Analytics Graduate Program
 
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Learn more at http://www.stjohns.edu/gradpremier/ms-data-mining
Views: 3088 St. John's University
Making Predictions with Data and Python : Predicting Credit Card Default | packtpub.com
 
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This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2eZbdPP]. Demonstrate how to build, evaluate and compare different classification models for predicting credit card default and use the best model to make predictions. • Introduce, load and prepare data for modeling • Show how to build different classification models • Show how to evaluate models and use the best to make predictions For the latest Big Data and Business Intelligence video tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 38183 Packt Video
Data Mining, Classification, Clustering, Association Rules, Regression, Deviation
 
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Complete set of Video Lessons and Notes available only at http://www.studyyaar.com/index.php/module/20-data-warehousing-and-mining Data Mining, Classification, Clustering, Association Rules, Sequential Pattern Discovery, Regression, Deviation http://www.studyyaar.com/index.php/module-video/watch/53-data-mining
Views: 92335 StudyYaar.com
Data science : R Predictive analytics with Decision Tree
 
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R - Decision Tree. Advertisements. Decision tree is a graph to represent choices and their results in form of a tree. The nodes in the graph represent an event or choice and the edges of the graph represent the decision rules or conditions. It is mostly used in Machine Learning and Data Mining applications using R. Video list in Tamil https://goo.gl/Pz2BPn Video list in English https://goo.gl/26f6T1 Data Download - http://atozknowledge.com/downloads/r/data1.csv YouTube channel link www.youtube.com/atozknowledgevideos Website http://atozknowledge.com/ Technology in Tamil & English
Views: 1285 atoz knowledge
Learning Predictive Analytics With Python, Analyzing Election Data With Pandas [Python Statistics]
 
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IN this Exploratory Data Analysis Tutorial, We perform predictive analytics with python by analyzing Election data from 2 candidates. Pandas data Analysis Techniques are used to learn about patterns in the election data. This is a Part of Python with Statistics Tutorial series. 🔷🔷🔷🔷🔷🔷🔷 Jupyter Notebooks and Data Sets for Practice: https://github.com/theengineeringworld/statistics-using-python 🔷🔷🔷🔷🔷🔷🔷 Python Graph Visualization, Statistics For Data Analytics [ Python Bar Graph Example Tutorial ] https://youtu.be/3KofFIhtjNE Data Cleaning Steps and Methods, How to Clean Data for Analysis With Pandas In Python [Example] 🐼 https://youtu.be/GMxCL0PBHzA Data Wrangling With Python Using Pandas, Data Science For Beginners, Statistics Using Python 🐍🐼 https://youtu.be/tqv3sL67sC8 Cleaning Data In Python Using Pandas In Data Mining Example, Statistics With Python For Data Science https://youtu.be/xcKXmXilaSw Cleaning Data In Python For Statistical Analysis Using Pandas, Big Data & Data Science For Beginners https://youtu.be/4own4ojgbnQ Exploratory Data Analysis In Python, Interactive Data Visualization [Course] With Python and Pandas https://youtu.be/VdWfB30QTYI Python Describe Statistics, Exploratory Data Analysis Using Pandas & NumPy [Descriptive Statistics] https://youtu.be/6SeJH0p7n44 Data Visualization In Python, [ Plots Of Two Variables ] Statistics & Data Analysis With Python 🐍 https://youtu.be/uufMAMUEAaQ Python Graph Visualization, Exploratory Data Analysis With Pandas & Matplotlib [ Python Statistic ] https://youtu.be/Eb9eD4aNS7o Python Data Visualization [ Graphing Categorical Data ] Pandas Data Analysis & Statistics Tutorial https://youtu.be/M1h0pPFVy0E Exploratory Data Analysis In Python, Email Analytics With Pandas [ Predictive Analytics Python ] 🔴 https://youtu.be/03OJrdbhor0 Learning Predictive Analytics With Python, Analyzing Election Data With Pandas [Python Statistics] https://youtu.be/sNg8VnMOAfw 🔷🔷🔷🔷🔷🔷🔷 *** Complete Python Programming Playlists *** * Python Data Science https://www.youtube.com/watch?v=Uct_EbThV1E&list=PLZ7s-Z1aAtmIbaEj_PtUqkqdmI1k7libK * NumPy Data Science Essential Training with Python 3 https://www.youtube.com/playlist?list=PLZ7s-Z1aAtmIRpnGQGMTvV3AGdDK37d2b * Python 3.6.4 Tutorial can be fund here: https://www.youtube.com/watch?v=D0FrzbmWoys&list=PLZ7s-Z1aAtmKVb0fpKyINNeSbFSNkLTjQ * Python Smart Programming in Jupyter Notebook: https://www.youtube.com/watch?v=FkJI8np1gV8&list=PLZ7s-Z1aAtmIVV0dp08_X-yDGrIlTExd2 * Python Coding Interview: https://www.youtube.com/watch?v=wwtzs7vTG50&list=PLZ7s-Z1aAtmJqtN1A3ydeMk0JoD3Lvt9g 📌📌📌📌📌📌📌📌📌📌
Views: 2625 TheEngineeringWorld
Data Mining with SAP Predictive Analysis - Data Geek Challenge 2013
 
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This video illustrates an example of how to build an end-to-end machine learned model using SAP Predictive Analysis. Furthermore the video walks you through the aspect of training your model with respect to BIAS in your data. The effect of incorrect sampling data from a BIAS sorted dataset is demonstrated. The dataset is based on the well known IRIS that is provided with R. Let me know if you would like a copy of the dataset so that you can try this yourself. Finally the machine trained model is then applied to new data in order to perform predictions.
Views: 2402 Kurt Holst
Data science : R Predictive analytics with Decision Tree {in தமிழ்}
 
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R - Decision Tree. Advertisements. Decision tree is a graph to represent choices and their results in form of a tree. The nodes in the graph represent an event or choice and the edges of the graph represent the decision rules or conditions. It is mostly used in Machine Learning and Data Mining applications using R. Video list in Tamil https://goo.gl/Pz2BPn Video list in English https://goo.gl/26f6T1 Data Download - http://atozknowledge.com/downloads/r/data1.csv YouTube channel link www.youtube.com/atozknowledgevideos Website http://atozknowledge.com/ Technology in Tamil & English
Views: 1576 atoz knowledge
Predictive Analytics Using R | Data Science With R |  Data Science Certification Training | Edureka
 
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** Data Science Certification using R: https://www.edureka.co/data-science ** This Edureka video on "Predictive Analytics Using R", will help you learn about how predictive analytics works and how it can be implemented using R to solve real-world problems. Below are the topics covered in this module: 0:56 What is Predictive Analytics? 2:02 Stages of Predictive Analytics 7:28 Predictive Analytics Using R 9:36 Predictive Analytics Use case 12:20 Demo Blog Series: http://bit.ly/data-science-blogs Data Science Training Playlist: http://bit.ly/data-science-playlist - - - - - - - - - - - - - - - - - Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Slideshare: https://www.slideshare.net/EdurekaIN/ - - - - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data lifecycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modeling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyze Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyze data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies. For online Data Science training, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.
Views: 4255 edureka!
Predictive Analytics & Machine Learning with SAP HANA
 
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Predictive Analytics & Machine Learning with SAP HANA combines the depth and speed of in-memory analytics with the power of native predictive algorithms. Together with SAP Predictive Analysis for visualization, R's extensive library of statistical and data mining techniques, and the SAP HANA predictive analytic library, you get everything you need to predict the future -- in real-time.
Views: 61687 SAP Technology
Data Mining and Predictive Analytics Final Project
 
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Modeling Analysis (Education Dataset) in SPSS
Views: 102 gong wen
Data Mining and Predictive Analytics in IBM SPSS Modeler
 
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The US faces a shortage of 1.5 million managers who know how to use the analysis of data to make effective decisions. McKinsey and Company. https://theachieveher.com/p/business-data-analytics-ibm-spss-modeler This predictive analytics course if for you if you are a … •Manager who wants to know how to use the analysis of data to make effective decisions. •Analyst who wants to understand data science even if you never intend to apply it yourself. •Anyone interested in learning about data mining. (IBM offers a free 30-day trial so let's get started!) •Scientist who wants to integrate text from your Twitter, Facebook or customer surveys into your predictive analysis. •Person who assesses proposals to improve some part of your organization’s business. •Beginner to IBM SPSS modeler 16 or 17 and looking for the best set of tutorials and demonstrations available online! •Data scientist who is just getting started with predictive analytics and wants to understand how to solve business problems with analytics in SPSS Modeler. So are you ready to easily and quickly answer data mining questions like: •Who are my best customers and what do they buy? •Why do they leave? •Which piece of equipment will fail next? •Or… which donors are likely to donate again? This course consists of extremely real world hands on demonstrations to immerse you in the most common prediction models, decision trees, clustering, and text analytics. So get ready to: 1.Segment your customers using popular models like K-Means. 2.Predict an amount of giving using several types of decision trees including C and R Trees. 3.Merge quantitative and qualitative data using text analytics. 4.Use a host of visual analytics like web and distribution nodes. 5.Use unsupervised clustering techniques to divide a population of customers into understandable groups. 6.Learn how to isolate the best input predictors using feature selection. 7.Export your insights to Excel and much more! Join me at https://theachieveher.com/p/business-data-analytics-ibm-spss-modeler
Using R and Apache Hadoop for Data Mining and Statistical Predictive Analytics
 
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This on-demand webinar, we'll: - Walk you through how Hadoop is being used today - Discuss real-world customer use cases for data mining and statistical predictive analytics in Hadoop - Show a live churn analytics demonstration with Revolution Analytics and Hortonworks Data Platform
Views: 10205 Hortonworks
The Buzz About Big Data:  How Predictive Analysis and Data Mining Affect Our World
 
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Wednesday, Oct. 9, 2013 John Carroll University International expert Colleen McCue, Ph.D. joins a panel of John Carroll faculty for a conversation about how big data analysis is affecting our lives and shaping our world.
RapidMiner Tutorial - Evaluation  (Data Mining and Predictive Analytics System)
 
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A tutorial discussing analytics evaluation with RapidMiner, an open source system for data mining, predictive analytics, machine learning, and artificial intelligence applications. For more information: http://rapid-i.com/ Brought to you by Rapid Progress Marketing and Modeling, LLC (RPM Squared) http://www.RPMSquared.com/
Views: 5477 Predictive Analytics
DI&A Slides: Descriptive, Prescriptive, and Predictive Analytics
 
01:01:59
Data analysis can be divided into descriptive, prescriptive and predictive analytics. Descriptive analytics aims to help uncover valuable insight from the data being analyzed. Prescriptive analytics suggests conclusions or actions that may be taken based on the analysis. Predictive analytics focuses on the application of statistical models to help forecast the behavior of people and markets. This webinar will compare and contrast these different data analysis activities and cover: - Statistical Analysis – forming a hypothesis, identifying appropriate sources and proving / disproving the hypothesis - Descriptive Data Analytics – finding patterns - Predictive Analytics – creating models of behavior - Prescriptive Analytics – acting on insight - How the analytic environment differs for each
Views: 2821 DATAVERSITY
RapidMiner Tutorial - Visualization  (Data Mining and Predictive Analytics System)
 
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A tutorial discussing some of the visualization capabilities of RapidMiner, an open source system for data mining, predictive analytics, machine learning, and artificial intelligence applications. For more information: http://rapid-i.com/ Brought to you by Rapid Progress Marketing and Modeling, LLC (RPM Squared) http://www.RPMSquared.com/
Views: 10512 Predictive Analytics
RapidMiner Tutorial - GUI Overview (Data Mining and Predictive Analytics Software)
 
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A tutorial overview of the RapidMiner GUI. RapidMiner is an open source system for data mining, predictive analytics, machine learning, and artificial intelligence applications. For more information: http://rapid-i.com/ Brought to you by Rapid Progress Marketing and Modeling, LLC (RPM Squared) http://www.RPMSquared.com/
Views: 3559 Predictive Analytics
K-Means Clustering Algorithm - Cluster Analysis | Machine Learning Algorithm | Data Science |Edureka
 
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( Data Science Training - https://www.edureka.co/data-science ) This Edureka k-means clustering algorithm tutorial video (Data Science Blog Series: https://goo.gl/6ojfAa) will take you through the machine learning introduction, cluster analysis, types of clustering algorithms, k-means clustering, how it works along with an example/ demo in R. This Data Science with R tutorial video is ideal for beginners to learn how k-means clustering work. You can also read the blog here: https://goo.gl/QM8on4 Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #kmeans #clusteranalysis #clustering #datascience #machinelearning How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "
Views: 77071 edureka!
Predictive Modelling Techniques | Data Science With R Tutorial
 
03:10:36
This lesson will teach you Predictive analytics and Predictive Modelling Techniques. Watch the New Upgraded Video: https://www.youtube.com/watch?v=DtOYBxi4AIE After completing this lesson you will be able to: 1. Understand regression analysis and types of regression models 2. Know and Build a simple linear regression model 3. Understand and develop a logical regression 4. Learn cluster analysis, types and methods to form clusters 5. Know more series and its components 6. Decompose seasonal time series 7. Understand different exponential smoothing methods 8. Know the advantages and disadvantages of exponential smoothing 9. Understand the concepts of white noise and correlogram 10. Apply different time series analysis like Box Jenkins, AR, MA, ARMA etc 11. Understand all the analysis techniques with case studies Regression Analysis: • Regression analysis mainly focuses on finding a relationship between a dependent variable and one or more independent variables. • It predicts the value of a dependent variable based on one or more independent variables • Coefficient explains the impact of changes in an independent variable on the dependent variable. • Widely used in prediction and forecasting Data Science with R Language Certification Training: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-r-tools-training?utm_campaign=Predictive-Analytics-0gf5iLTbiQM&utm_medium=SC&utm_source=youtube #datascience #datasciencetutorial #datascienceforbeginners #datasciencewithr #datasciencetutorialforbeginners #datasciencecourse The Data Science with R training course has been designed to impart an in-depth knowledge of the various data analytics techniques which can be performed using R. The course is packed with real-life projects, case studies, and includes R CloudLabs for practice. Mastering R language: The course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R. Mastering advanced statistical concepts: The course also includes the various statistical concepts like linear and logistic regression, cluster analysis, and forecasting. You will also learn hypothesis testing. As a part of the course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and Internet. R CloudLab has been provided to ensure a practical and hands-on experience. Additionally, we have four more projects for further practice. Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 219795 Simplilearn
DePaul University Center for Data Mining & Predictive Analytics - Mary Jo
 
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DePaul University graduate student Mary Jo Zefeldt discusses the importance of a degree in analytics, and shares her excitement around the new Center for Data Mining and Predictive Analytics.
Views: 1231 timjpowers
Predictive and Prescriptive Analytics
 
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In this video I will clarify the definition of Descriptive Analytics, Predictive Analytics and what is Prescriptive analytics.
24 Predictive Analytics Training with Weka (Classification by regression)
 
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Data Mining and Predictive Analytics training course using the open source Weka tool. Videos producted by the University of Waikato, New Zealand. Posted by Rapid Progress Marketing and Modeling, LLC (RPM2) under CC BY 3.0 RPM2 is a full-service Predictive Analytics and Data Sciences Services company specializing in Model Development, Consulting, Direct Marketing Services, and Professional Training. Visit us at http://www.RPMSquared.com/
Views: 7933 Predictive Analytics
Predicting Football Matches Using Data With Jordan Tigani - Strata Europe 2014
 
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A keynote address from Strata + Hadoop World Europe 2014 in Barcelona, "Predictive Analytics in the Cloud: Predicting Football." Watch more from Strata Europe 2014: http://goo.gl/uqw6WS Visit the Strata website to learn more: http://strataconf.com/strataeu2014/ Subscribe for more from the conference! http://goo.gl/szEauh How can you turn raw data into predictions? How can you take advantage of both cloud scalability and state-of-the-art Open Source Software? This talk shows how we built a model that correctly predicted the outcome of 14 of 16 games in the World Cup using Google’s Cloud Platform and tools like iPython and StatsModels. I’ll also demonstrate new tools to integrate iPython with Google’s cloud and how you can use the same tools to make your own predictions. About Jordan Tigani (Google): Jordan Tigani has more than 15 years of professional software development experience, the last 4 of which have been spent building BigQuery. Prior to joining Google, Jordan worked at a number of star-crossed startups, where he learned to make data-based predictions. He is a co-author of Google BigQuery Analytics. When not analyzing soccer matches, he can often be found playing in one. Stay Connected to O'Reilly Media by Email - http://goo.gl/YZSWbO Follow O'Reilly Media: http://plus.google.com/+oreillymedia https://www.facebook.com/OReilly https://twitter.com/OReillyMedia
Views: 97486 O'Reilly
DePaul University Center for Data Mining & Predictive Analytics - Jonathan F.
 
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DePaul University graduate student Jonathan Feigenbaum discusses the importance of a degree in analytics, and shares his excitement around the new Center for Data Mining and Predictive Analytics.
Views: 1270 timjpowers
DePaul University Center for Data Mining & Predictive Analytics - Jonathan G.
 
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DePaul University graduate student Jonathan Gemmel discusses the importance of a degree in analytics, and shares his excitement around the new Center for Data Mining and Predictive Analytics.
Views: 1197 timjpowers